Computer scientists at Rice University, Argonne National Laboratory, and the University of Illinois at Urbana-Champaign say “inexact computing” can dramatically improve the quality of simulations run on supercomputers. Inexact computing focuses on saving energy wherever possibly by paying only for the accuracy that is required in a given situation, says Krishna Palem, director of Rice’s Center for Computing at the Margins. Using the Newton-Raphson tool of numerical analysis, the team demonstrated it is possible to leapfrog from one part of a computation to the next and reinvest the energy saved from inexact computations at each new leap to increase the quality of the final answer while retaining the same energy budget. The researchers showed the solution’s quality could be improved by more than three orders of magnitude for a fixed energy cost when an inexact approach to calculation was applied instead of a traditional high-precision approach. Palem compares their approach to calculating answers as a relay of sprints rather than a marathon. “A specific goal is to encourage the application of this approach as a way to advance the quality of weather and climate modeling by improving model resolution,” he says.